awesome-2vec

Why we included this project

This list is a field map for anyone trying to make sense of the many embedding models built in the word2vec style, letting you skip the usual hunt through papers and scattered repos by grouping each model with its original paper and a working Python or C++ implementation. It covers text models like word2vec and doc2vec alongside graph and network embedders such as Walklets, Splitter, AttentionWalk, and role2vec, which makes it a useful starting point when you need to compare approaches before picking one for your own project. It is especially handy if you are new to graph and network embedding research, since most entries point to runnable code rather than papers alone. One thing to keep in mind: this is a reading resource, not software you install, and you pull the code from the linked repositories yourself. The list also deliberately points network-specific models to a companion list, which keeps the main page easy to browse.